Clinical value of Lipoprotein(a) combined with CatLet coronary score in predicting adverse events after emergency PCI for AMI patients.
Lipoprotein(a) [Lp(a)] promotes atherosclerotic plaque vulnerability through pro-inflammatory and thrombogenic pathways, while the CatLet© angiographic score quantifies coronary lesion complexity. We hypothesized that their integration would improve prognostication in acute myocardial infarction (AMI) after emergency percutaneous coronary intervention (ePCI).
In this retrospective cohort, 307 AMI patients undergoing successful ePCI (2020-2022) were stratified by 1-year major adverse cardiovascular/cerebrovascular events (MACCE). Serum Lp(a) and troponin I were measured post-admission. CatLet© and Gensini scores were assessed by blinded analysts. Multivariable logistic regression and ROC analyses evaluated predictive performance.
MACCE patients (n = 78) exhibited higher Lp(a) (135.99 ± 33.07vs. 123.35 ± 42.70nmol/L, P = 0.0178) and CatLet© scores (33.58 ± 9.04vs. 30.80 ± 8.24, P = 0.0012) versus controls. Lp(a) (OR=2.339,95%CI:1.519-3.603, P < 0.001) and CatLet© score (OR=1.092, 95%CI:1.027-1.161, P = 0.005) independently predicted MACCE. The combined model Lp(a)≥70.70 nmol/L + CatLet© ≥ 18.6) significantly outperformed individual markers (AUC 0.862 [95%CI:0.83-0.96] vs. 0.780/0.833; DeLong's test confirmed the superiority of the combined model over individual predictors (P = 0.0089, Z = 2.64 vs. Lp(a); P = 0.034, Z = 2.12 vs. CatLet© score), with 88% sensitivity and 83% specificity.
The Lp(a)-CatLet© synergy enhances MACCE risk stratification in ePCI-treated AMI, reflecting complementary pathobiological (Lp(a)-driven plaque vulnerability) and anatomical (CatLet©-quantified complexity) pathways. This dual-parameter approach could support post-PCI risk stratification and follow-up planning.
In this retrospective cohort, 307 AMI patients undergoing successful ePCI (2020-2022) were stratified by 1-year major adverse cardiovascular/cerebrovascular events (MACCE). Serum Lp(a) and troponin I were measured post-admission. CatLet© and Gensini scores were assessed by blinded analysts. Multivariable logistic regression and ROC analyses evaluated predictive performance.
MACCE patients (n = 78) exhibited higher Lp(a) (135.99 ± 33.07vs. 123.35 ± 42.70nmol/L, P = 0.0178) and CatLet© scores (33.58 ± 9.04vs. 30.80 ± 8.24, P = 0.0012) versus controls. Lp(a) (OR=2.339,95%CI:1.519-3.603, P < 0.001) and CatLet© score (OR=1.092, 95%CI:1.027-1.161, P = 0.005) independently predicted MACCE. The combined model Lp(a)≥70.70 nmol/L + CatLet© ≥ 18.6) significantly outperformed individual markers (AUC 0.862 [95%CI:0.83-0.96] vs. 0.780/0.833; DeLong's test confirmed the superiority of the combined model over individual predictors (P = 0.0089, Z = 2.64 vs. Lp(a); P = 0.034, Z = 2.12 vs. CatLet© score), with 88% sensitivity and 83% specificity.
The Lp(a)-CatLet© synergy enhances MACCE risk stratification in ePCI-treated AMI, reflecting complementary pathobiological (Lp(a)-driven plaque vulnerability) and anatomical (CatLet©-quantified complexity) pathways. This dual-parameter approach could support post-PCI risk stratification and follow-up planning.